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Development of Data Mining Framework Cardiovascular Disease Prediction

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The Effect of Information Technology on Business and Marketing Intelligence Systems

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1056))

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Abstract

One of the highest shares of data-driven technology of health sector happens for private insurance stakeholders. It is therefore clear that private insurance companies can only survive being competitive in covering different medical stages such as surgery, intervention and other clinical trials in a high-risk environment. Estimation of expected costs and coverage is also important for both patient and insurer. In this case study we as a Data Mining and Artificial Business consultant want to explore different techniques of data mining to find out business risks for patients. We have asked the insurer to provide us a sizable medical history to watch those features. We would like to predict if given biographical profile of the patient along with exam results can predict CVD so he can cover his costs with this Insurer. On the other hand, in case of higher error of misclassified CVD what kind of decision should be taken by risk holder and insurer. Which one of these attributes causing this cost and what other stakeholders like target group of patients can be suffered from the loss? The ultimate goal is to develop a model that can predict the gap between those patients’ perception of their disease and their real disease. This can further help stakeholders to develop specific insurance policy.

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Author information

Authors and Affiliations

  1. Faculty of Management, Canadian University Dubai, Dubai, UAE

    Raed A. Said

  2. Department of Computer Engineering, College of Engineering, Mutah University, Mu’tah, Jordan

    Nidal A. Al-Dmour

  3. College of Engineering and Information Technology, University of Science and Technology of Fujairah, Fujairah, UAE

    Mohammed Salahat

  4. School of Information Technology, Skyline University College, Sharjah, UAE

    Ghassan F. Issa

  5. School of Business, Skyline University College, Sharjah, UAE

    Haitham M. Alzoubi

  6. Department of Marketing, School of Business, University of Jordan, Amman, Jordan

    Muhammad Alshurideh

  7. Department of Management, College of Business Administration, University of Sharjah, Sharjah, UAE

    Muhammad Alshurideh

Authors
  1. Raed A. Said
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  2. Nidal A. Al-Dmour
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  3. Mohammed Salahat
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  4. Ghassan F. Issa
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  5. Haitham M. Alzoubi
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  6. Muhammad Alshurideh
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Correspondence to Haitham M. Alzoubi .

Editor information

Editors and Affiliations

  1. Dept of Mngmnt, Cllg of Busness Admin, University of Sharjah, Sharjah, United Arab Emirates

    Muhammad Alshurideh

  2. Department of Business Administration, Faculty of Economics and Administrative Sciences, Hashemite University, Zarqa, Jordan

    Barween Hikmat Al Kurdi

  3. Management Information Systems Department, School of Business, University of Jordan, Aqaba, Jordan

    Ra’ed Masa’deh

  4. Skyline University College, Sharjah, United Arab Emirates

    Haitham M. Alzoubi

  5. Research Institute of Sciences and Engineering, University of Sharjah, Sharjah, United Arab Emirates

    Said Salloum

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Said, R.A., Al-Dmour, N.A., Salahat, M., Issa, G.F., Alzoubi, H.M., Alshurideh, M. (2023). Development of Data Mining Framework Cardiovascular Disease Prediction. In: Alshurideh, M., Al Kurdi , B.H., Masa’deh, R., Alzoubi , H.M., Salloum, S. (eds) The Effect of Information Technology on Business and Marketing Intelligence Systems. Studies in Computational Intelligence, vol 1056. Springer, Cham. https://doi.org/10.1007/978-3-031-12382-5_114

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  • DOI: https://doi.org/10.1007/978-3-031-12382-5_114

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